John Prager

IBM Watson: Building a Question-Answering system to Beat Humans on TV

Zeit: Mon 30.5.2016, 15:45, 90 Minuten
Ort: HS 18

Zusammenfassung

In February of 2011, IBM's computer system called Watson participated in the US game show
Jeopardy! on national television against two former champions - and won. Jeopardy! is a questionanswering
challenge, which, despite including elements of speed and betting, is at its core about
finding answers to questions and having a good confidence estimate about those answers.
Question-answering (QA) is a sub-field of Artificial Intelligence, and Watson is acknowledged to
represent the current state-of-the-art. Watson is able to answer some obscure general-knowledge
questions that average people have difficulty with, so in that very limited and technical sense is
super-human. On the other hand it makes regular mistakes, usually in regard to questions about
common sense or common human experience (of which it has none). This talk will examine what
went into Watson, to what extent it actually understands the domain it operates in, and where the
technology is headed.

Vortragender

John Prager has been working in technical fields related directly or indirectly to Question Answering
for most of his professional career. Most recently, while at the IBM T.J. Watson Research Center
he has been part of the Watson project, a system that played (and won) the Jeopardy! TV quizshow
game. He has been involved in both the algorithms area, concentrating on question analysis
and wordplay, and strategy. He is still involved with Watson, as it is being adapted to clinical
decision support in the health-care domain. Previously, he led IBM?s successful entries in the
TREC-QA tasks, an annual evaluation at NIST. Prior to that, he worked in various areas of Search,
including Language Identification, Web Search and Categorization. While at the former IBM
Cambridge Scientific Center (Cambridge, Mass), John was the project leader of the REASON (Realtime
Explanation And SuggestiON) project; REASON would provide users help by taking naturallanguage
questions and processing them with an inference engine tied to a large repository of facts
and rules about network-wide resources. John has degrees in Mathematics and Computer Science
from the University of Cambridge (Cambridge, UK) and in Artificial Intelligence from the University of
Massachusetts; his publications include conference and journal papers, fifteen patents, and a book
on Turing.